LIDAR systems employ pulses of light to measure distance to an object based on the time of flight (TOF) of the pulsed of light. A pulse of light emitted from a light source of the LIDAR system interacts with a distal object. A portion of the light reflects from the object and returns to a detector of the LIDAR system. Based on the time elapsed between emission of the pulse of light and detection of the returned pulse of light, a distance is estimated.
In some examples, a pulsed laser emitter is employed to generated light pulses. The light pulses are focused through a lens or lens assembly. The time it takes for that pulse of light to return to a detector mounted near the emitter is measured. A distance is derived from the time measurement with high accuracy.
In some examples, multiple pulses are emitted in rapid succession, and the direction of those emissions is sequentially varied. In these examples, each distance measurement can be considered a pixel, and a collection of pixels emitted and captured in rapid succession (i.e., “point cloud”) can be rendered as an image or analyzed for other reasons (e.g., detecting obstacles). In some examples, viewing software is employed to render the resulting point clouds as images that appear three dimensional to a user. Different schemes can be used to depict the distance measurements as 3-D images that appear as if they were captured by a live action camera.
Some LIDAR systems employ a single laser emitter/detector combination combined with a rotating mirror to effectively scan across a plane. Distance measurements performed by such a system are effectively two dimensional (i.e., planar), and the captured distance points are rendered as a 2-D (i.e. single plane) point cloud.
In some examples, rotating mirrors are rotated at very fast speeds—in the thousands of RPMs. As stated above, this design inherently renders only a 2-D point cloud. However, a 3-D point cloud is often required. The other dimension is provided for in a number of ways. Most often, the entire instrument is actuated up and down and/or back and forth, often on a gimbal—a process known within the art as winking or nodding the sensor. Thus, a single beam lidar unit can be employed to capture an entire 3-D array of distance points, albeit one point at a time. In a related example, a prism is employed to “divide” the laser pulse into multiple layers, each having a slightly different vertical angle. This simulates the nodding effect described above, but without actuation of the sensor itself.
In all the above examples, the main premise is a single laser emitter/detector combination, where the light path is somehow altered to achieve a broader field of view than a single sensor. The device is inherently limited to the number of pixels it can generate due to the limitation of how many pulses per second are possible from a single laser. Any alteration of the beam path, whether it is by mirror, prism, or actuation of the device, causes the point cloud to be less dense, but cover a broader area.
As noted above, 3-D point cloud systems exist in several configurations. However, in many applications it is necessary to see over a broad field of view. For example, in an autonomous vehicle application, the vertical field of view should extend above the horizon, in case the car enters a dip in the road, and should extend down as close as possible to see the ground in front of the vehicle. In addition, it is necessary to have a minimum of delay between the actions happening in the real world and the imaging of those actions. In some examples, it is desirable to provide a complete image update at least five times per second.
Improvements in field of view and the point cloud density of 3-D imaging systems are desired.